We propose a novel Neural Radiance Field (NeRF) representation for non-opaque scenes that enables fast inference by utilizing textured polygons. Despite the high-quality novel view rendering that NeRF provides, a critical limitation is that it relies on volume rendering that can be computationally expensive and does not utilize the advancements in modern graphics hardware. Many existing methods fall short when it comes to modelling volumetric effects as they rely purely on surface rendering. We thus propose to model the scene with polygons, which can then be used to obtain the quadrature points required to model volumetric effects, and also their opacity and colour from the texture. To obtain such polygonal mesh, we train a specialized field whose zero-crossings would correspond to the quadrature points when volume rendering, and perform marching cubes on this field. We then perform ray-tracing and utilize the ray-tracing shader to obtain the final colour image. Our method allows an easy integration with existing graphics frameworks allowing rendering speed of over 100 frames-per-second for a $1920\times1080$ image, while still being able to represent non-opaque objects.

翻译：我们提出了一种用于非不透明场景的新型神经辐射场（NeRF）表示方法，该方法通过利用纹理多边形实现快速推理。尽管NeRF提供了高质量的新视角渲染，但其一个关键局限在于它依赖于体绘制，这可能导致计算成本高昂且未能充分利用现代图形硬件的进步。许多现有方法在建模体效应方面存在不足，因为它们纯粹依赖于表面渲染。因此，我们提出使用多边形对场景进行建模，这些多边形随后可用于获取建模体效应所需的积分点，并从纹理中获取其不透明度和颜色。为获得此类多边形网格，我们训练了一个专用场，其零交叉点在体绘制时将对应积分点，并在此场上执行行进立方体算法。随后，我们进行光线追踪并利用光线追踪着色器获取最终彩色图像。我们的方法能够轻松与现有图形框架集成，在$1920\times1080$分辨率下实现超过100帧/秒的渲染速度，同时仍能表示非不透明物体。